Damodaran Senthilkumar, Miya Jharna, Kautto Esko, Zhu Eliot, Samorodnitsky Eric, Datta Jharna, Reeser Julie W, Roychowdhury Sameek
Division of Medical Oncology, Department of Internal Medicine, The Ohio State University, Columbus, Ohio.
Comprehensive Cancer Center, The Ohio State University, Columbus, Ohio.
J Mol Diagn. 2015 Sep;17(5):554-9. doi: 10.1016/j.jmoldx.2015.05.002.
Massively parallel sequencing technologies have enabled characterization of genomic alterations across multiple tumor types. Efforts have focused on identifying driver mutations because they represent potential targets for therapy. However, because of the presence of driver and passenger mutations, it is often challenging to assign the clinical relevance of specific mutations observed in patients. Currently, there are multiple databases and tools that provide in silico assessment for potential drivers; however, there is no comprehensive resource for mutations with functional characterization. Therefore, we created an expert-curated database of potentially actionable driver mutations for molecular pathologists to facilitate annotation of cancer genomic testing. We reviewed scientific literature to identify variants that have been functionally characterized in vitro or in vivo as driver mutations. We obtained the chromosome location and all possible nucleotide positions for each amino acid change and uploaded them to the Cancer Driver Log (CanDL) database with associated literature reference indicating functional driver evidence. In addition to a simple interface, the database allows users to download all or selected genes as a comma-separated values file for incorporation into their own analysis pipeline. Furthermore, the database includes a mechanism for third-party contributions to support updates for novel driver mutations. Overall, this freely available database will facilitate rapid annotation of cancer genomic testing in molecular pathology laboratories for mutations.
大规模平行测序技术已能够对多种肿瘤类型的基因组改变进行表征。研究工作主要集中在识别驱动突变,因为它们代表了潜在的治疗靶点。然而,由于存在驱动突变和乘客突变,确定在患者中观察到的特定突变的临床相关性往往具有挑战性。目前,有多个数据库和工具可提供对潜在驱动因素的计算机评估;然而,对于具有功能特征的突变,尚无全面的资源。因此,我们为分子病理学家创建了一个由专家精心策划的潜在可操作驱动突变数据库,以促进癌症基因组检测的注释。我们查阅了科学文献,以识别在体外或体内已被功能表征为驱动突变的变体。我们获取了每个氨基酸变化的染色体位置和所有可能的核苷酸位置,并将它们上传到癌症驱动日志(CanDL)数据库,同时附上表明功能驱动证据的相关文献参考。除了一个简单的界面外,该数据库还允许用户将所有或选定的基因下载为逗号分隔值文件,以便纳入他们自己的分析流程。此外,该数据库还包括一种第三方贡献机制,以支持对新的驱动突变进行更新。总体而言,这个免费提供的数据库将有助于分子病理实验室对癌症基因组检测中的突变进行快速注释。